Abstract
Abstract Follicular lymphoma (FL), a form of non-Hodgkin lymphoma, is the second most common form of B-cell lymphoma and remains incurable in the majority of cases despite recent advances in therapy. Following an indolent phase, 50% of patients suffer disease transformation to an aggressive form of lymphoma (transformed FL; tFL). This dramatic switch in disease behavior typically culminates in rapid deterioration and patient demise. Accordingly, much effort has been focused on understanding the genetics of transformation and has resulted in the identification of key genetic lesions (e.g. MYC activation, loss of p53, cell cycle controls, activation of NFKB (TNFAIp3/A20)). However, exactly how tumor metabolism, which is altered by these genetic lesions, contributes to disease aggressiveness is not known and therefore the metabolic changes that occur upon FL transformation are poorly understood. We have developed a murine model of FL transformation that recapitulates key genetic and pathological aspects of human FL (Oricchio et al, 2011). This model allows us to study the genetics and metabolism of FL transformation. Specifically, we will systematically define the metabolic profiles of genetically defined murine lymphomas that represent different stages of transformation and cross-compare metabolic changes to primary patient samples. This ensures focus on clinically relevant changes and provides metabolic annotation of distinct tumor genotypes. This study builds on the complementary strengths of the Le lab (Johns Hopkins) in cancer metabolism and the Wendel lab (MSKCC) in modeling FL genetics. Our study shows that MYC transformed FL exhibits a distinct metabolic profile as compared to indolent follicular lymphoma or normal spleen. The most altered pathways examined thus far are glycolysis and amino acid metabolism. We believe that the transformed lymphoma is more reliant upon glycolysis and may be exhibiting aerobic glycolysis, also known as the Warburg Effect. This is substantiated from previous experiments in which a Burkitt lymphoma line, also overexpressing MYC, was found to have altered glycolytic intermediates levels. We next plan to examine the metabolic profile of other transformed follicular lymphoma models of known genetic backgrounds. We will also cross validate the transformed mouse models with follicular lymphoma patient samples of known genetic backgrounds to identify potential metabolic markers. Citation Format: Brad Poore, Ana Ortega-Molina, Christopher Nguyen, Liang Zhao, Anne Blackwell, Thomas Hartung, Hans-Guido Wendel, Anne Le. Metabolic characterization of follicular lymphoma transformation. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1183. doi:10.1158/1538-7445.AM2015-1183
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